Forecasting Inflation using Functional Time Series Analysis

Raja Fawad Zafar, Abdul Qayyum and Saghir Pervaiz Ghouri
Authors registered in the RePEc Author Service: Saghir Pervaiz Ghauri

MPRA Paper from University Library of Munich, Germany

Abstract: In present study we model the data using Functional Time series Analysis (FTSA). The method is basically univariate, so to check its efficiency we compared it with seasonal ARIMA models. We have used data sets of monthly frequency from 2002-2011 to forecast Consumer Price Index (CPI) of Pakistan. We withhold some data of last year (i.e. of 2011) and based on remaining year (2002-2010) we fitted model and forecasted the values of monthly CPI. Our study compares the performance of FTSA model and ARIMA model using the test data of 2011. Comparison based on forecast evaluation criteria’s and forecasted value of 2011, indicates that FTSA model using CPI general data outperforms SARIMA models

Keywords: Forecasting; Inflation; SARIMA; FTSA (search for similar items in EconPapers)
JEL-codes: C22 C53 (search for similar items in EconPapers)
Date: 2015-03-20
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-pr~
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